Transportation planning with drop trailer arrangements

ABSTRACT

Systems, methodologies, media, and other embodiments associated with transportation planning in light of drop trailer arrangements are described. One exemplary computer-implemented method embodiment includes receiving orders that describe items to be delivered to facilities as controlled by order requirements. The method may also include accessing a transportation planning model that includes information concerning shipping modes and carriers by which an order can be delivered to a facility. The transportation planning model may also include data concerning drop trailer arrangements between facilities and the carriers. The method may also include selectively consolidating orders into shipments based on the transportation planning model and the availability of a drop trailer arrangement. The method may also include selectively assigning shipments to loads based on the transportation planning model and the availability of a drop trailer action. The method may output an actionable plan of loads stored, for example, on a computer-readable medium.

BACKGROUND

Transportation planning systems and methods may attempt to minimizetransportation costs through actions like load consolidation, continuousmoves, selecting carriage mode, selecting carrier, and so on.Transportation planning systems and methods may also attempt to improvesituations like on-time delivery, customer satisfaction, compliance withrouting guides, usage of preferred carriers, usage of volume-basedpricing, and so on. At times these may produce conflicting and/orcompeting goals. Thus, transportation planning systems and methods maybe configured to selectively make trade-offs in order to maximize, forexample, an overall utility.

Transportation planning generally concerns determining how and when toship items from sources to destinations. As used herein, transportationplanning concerns determining how and when to ship items using vehicles(e.g., trucks) that may have a leave-behind and/or pickup capability(e.g., drop trailer arrangement) available at a location. While trucksare primarily described, it is to be appreciated that vehicles likeroll-on roll-off airplanes, roll-on roll-off ships, trains, and the likemay also have leave-behind and/or pickup capability.

A leave-behind and/or pickup capability like a drop-trailer arrangementis contrasted with a live (un)load situation. In a live (un)loadsituation, a driver stops and waits while his truck is (un)loaded. In adrop trailer arrangement, a driver delivers a trailer, unhooks it, andmay hook up and leave with another trailer. Thus, the driver does notwait while the trailer is (un)loaded. Similarly, in some cases, a trainmay deliver a train car, be uncoupled from it and coupled to anotherwithout waiting for the car to be (un)loaded. Likewise, in some cases, aplane may deliver a first container, pick up a second container and takeoff with the second container rather than waiting around for the firstcontainer to be (un)loaded. Similarly, a ship may deliver a container,and receive another container without waiting for the container to beunloaded and reloaded.

To illustrate how a drop trailer arrangement may work, consider afacility that has a drop trailer arrangement with a specific carrier fora specific type of equipment (e.g., trailer). Due to the drop trailerarrangement, the facility may develop a “pool” of vehicles (e.g.,trailers) of the specific type belonging to the specific carrier.Trailers in the pool may be in different states like loaded, unloaded,awaiting pickup, and so on.

With the pool of trailers available at the facility, a certainflexibility may be applied to delivering (un)loaded trailers to thefacility and/or to picking up (un)loaded trailers from the facility. Theflexibility may derive from only requiring the time/space/personnel to(un)hook a trailer(s) rather than requiring the time/space/personnel todock and (un)load a trailer(s).

Consider a multi-stop load where a truck and trailer are loaded at asource location with a set of shipments. The truck and trailer maytravel to a first location, wait while a first shipment is unloaded, maycontinue to a second location, wait while a second shipment is unloaded,and may then arrive at a third location where the carrier and thefacility have a drop trailer arrangement for this type of trailer.Rather than wait while the third shipment is unloaded, the trailer maybe unhooked and left for later unloading. Additionally, another trailer,either empty or loaded, may be available for the truck to hook up anddrive away. When there is a pickup for each drop off the size of thepool of trailers may remain substantially constant and act as a bufferthat may relieve time pressures associated with live (un)loading. Also,having a pool of trailers may facilitate improving dock workerutilization at a facility by facilitating a steady workflow from thepool rather than a hit or miss workflow common in non-bufferedsituations.

Note that in a multi-stop load like that described above, the load istypically arranged so that the facility with the drop trailerarrangement is visited last.

Unique elements of the North American regional transportation systemlead to extensive truck utilization. The unique elements include longdistances between major cities, an extensive high quality, governmentsubsidized road network, relatively low fuel costs, a highly organizedand competitive trucking industry, comparatively poor rail service overa relatively limited rail network, and a high level of economic activityover very dense traffic lanes. Thus, systems and methods thatparticipate in truck based transportation planning may facilitatemitigating some inefficiencies associated with truck utilization.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, which are incorporated in and constitute apart of the specification, illustrate various example systems, methods,and other example embodiments of various aspects of the invention. Itwill be appreciated that the illustrated element boundaries (e.g.,boxes, groups of boxes, or other shapes) in the figures represent oneexample of the boundaries. One of ordinary skill in the art willappreciate that one element may be designed as multiple elements or thatmultiple elements may be designed as one element. An element shown as aninternal component of another element may be implemented as an externalcomponent and vice versa. Furthermore, elements may not be drawn toscale.

FIG. 1 illustrates an example method associated with transportationplanning in light of drop trailer arrangements.

FIG. 2 illustrates another example method associated with transportationplanning in light of drop trailer arrangements.

FIG. 3 illustrates an example system associated with transportationplanning in light of drop trailer arrangements.

FIG. 4 illustrates another example system associated with transportationplanning in light of drop trailer arrangements.

FIG. 5 illustrates an example computing environment in which examplesystems and methods illustrated herein can operate.

FIG. 6 illustrates an example data packet and illustrates examplesubfields within the example data packet.

FIG. 7 illustrates an example application programming interface (API).

FIG. 8 illustrates example pooling scenarios.

FIG. 9 illustrates example multi-stop load scenarios.

DETAILED DESCRIPTION

Example systems, methods, media, and other embodiments described hereinrelate to transportation planning in light of drop trailer arrangements.In one example, computer-based systems and methods that may consolidateorders, plan loads, and/or assign consolidated orders to loads may beconfigured to consider drop-trailer arrangements when consolidating,planning, and/or assigning. In another example, computer-based systemsand methods that consolidate orders, route loads, and assign orders toloads may be reconfigured to re-examine consolidation, routing, and/orassigning decisions based on post-calculation examination ofdrop-trailer arrangements.

The following includes definitions of selected terms employed herein.The definitions include various examples and/or forms of components thatfall within the scope of a term and that may be used for implementation.The examples are not intended to be limiting. Both singular and pluralforms of terms may be within the definitions.

In the context of transportation planning and this application, “load”refers to a set of shipments assigned to a vehicle and assigned aschedule for delivery. A load may refer to a single stop load, amulti-stop load, and the like.

As used in this application, the term “computer component” refers to acomputer-related entity, either hardware, firmware, software, acombination thereof, or software in execution. For example, a computercomponent can be, but is not limited to being, a process running on aprocessor, a processor, an object, an executable, a thread of execution,a program, and a computer. By way of illustration, both an applicationrunning on a server and the server can be computer components. One ormore computer components can reside within a process and/or thread ofexecution and a computer component can be localized on one computerand/or distributed between two or more computers.

“Computer communication”, as used herein, refers to a communicationbetween two or more computing devices (e.g., computer, personal digitalassistant, cellular telephone) and can be, for example, a networktransfer, a file transfer, an applet transfer, an email, a hypertexttransfer protocol (HTTP) transfer, and so on. A computer communicationcan occur across, for example, a wireless system (e.g., IEEE 802.11), anEthernet system (e.g., IEEE 802.3), a token ring system (e.g., IEEE802.5), a local area network (LAN), a wide area network (WAN), apoint-to-point system, a circuit switching system, a packet switchingsystem, and so on.

“Computer-readable medium”, as used herein, refers to a medium thatparticipates in directly or indirectly providing signals, instructionsand/or data. A computer-readable medium may take forms, including, butnot limited to, non-volatile media, volatile media, and transmissionmedia. Non-volatile media may include, for example, optical or magneticdisks and so on. Volatile media may include, for example, semiconductormemories, dynamic memory and the like. Transmission media may includecoaxial cables, copper wire, fiber optic cables, and the like.Transmission media can also take the form of electromagnetic radiation,like that generated during radio-wave and infra-red data communications,or take the form of one or more groups of signals. Common forms of acomputer-readable medium include, but are not limited to, a floppy disk,a flexible disk, a hard disk, a magnetic tape, other magnetic medium, aCD-ROM, other optical medium, punch cards, paper tape, other physicalmedium with patterns of holes, a RAM (random access memory), a ROM (readonly memory), an EPROM, a FLASH-EPROM, or other memory chip or card, amemory stick, a carrier wave/pulse, and other media from which acomputer, a processor or other electronic device can read. Signals usedto propagate instructions or other software over a network, like theInternet, can be considered a “computer-readable medium.”

“Data store”, as used herein, refers to a physical and/or logical entitythat can store data. A data store may be, for example, a database, atable, a file, a list, a queue, a heap, a memory, a register, and so on.A data store may reside in one logical and/or physical entity and/or maybe distributed between two or more logical and/or physical entities.

“Logic”, as used herein, includes but is not limited to hardware,firmware, software and/or combinations of each to perform a function(s)or an action(s), and/or to cause a function or action from anotherlogic, method, and/or system. For example, based on a desiredapplication or needs, logic may include a software controlledmicroprocessor, discrete logic like an application specific integratedcircuit (ASIC), an analog circuit, a digital circuit, a programmed logicdevice, a memory device containing instructions, or the like. Logic mayinclude one or more gates, combinations of gates, or other circuitcomponents. Logic may also be fully embodied as software. Where multiplelogical logics are described, it may be possible to incorporate themultiple logical logics into one physical logic. Similarly, where asingle logical logic is described, it may be possible to distribute thatsingle logical logic between multiple physical logics.

An “operable connection”, or a connection by which entities are“operably connected”, is one in which signals, physical communications,and/or logical communications may be sent and/or received. Typically, anoperable connection includes a physical interface, an electricalinterface, and/or a data interface, but it is to be noted that anoperable connection may include differing combinations of these or othertypes of connections sufficient to allow operable control. For example,two entities can be operably connected by being able to communicatesignals to each other directly or through one or more intermediateentities like a processor, operating system, a logic, software, or otherentity. Logical and/or physical communication channels can be used tocreate an operable connection.

“Signal”, as used herein, includes but is not limited to one or moreelectrical or optical signals, analog or digital signals, data, one ormore computer or processor instructions, messages, a bit or bit stream,or other means that can be received, transmitted and/or detected.

“Software”, as used herein, includes but is not limited to, one or morecomputer or processor instructions that can be read, interpreted,compiled, and/or executed and that cause a computer, processor, or otherelectronic device to perform functions, actions and/or behave in adesired manner. The instructions may be embodied in various forms likeroutines, algorithms, modules, methods, threads, and/or programsincluding separate applications or code from dynamically linkedlibraries. Software may also be implemented in a variety of executableand/or loadable forms including, but not limited to, a stand-aloneprogram, a function call (local and/or remote), a servelet, an applet,instructions stored in a memory, part of an operating system or othertypes of executable instructions. It will be appreciated by one ofordinary skill in the art that the form of software may be dependent on,for example, requirements of a desired application, the environment inwhich it runs, and/or the desires of a designer/programmer or the like.It will also be appreciated that computer-readable and/or executableinstructions can be located in one logic and/or distributed between twoor more communicating, co-operating, and/or parallel processing logicsand thus can be loaded and/or executed in serial, parallel, massivelyparallel and other manners.

Suitable software for implementing the various components of the examplesystems and methods described herein include programming languages andtools like Java, Pascal, C#, C++, C, CGI, Perl, SQL, APIs, SDKs,assembly, firmware, microcode, and/or other languages and tools.Software, whether an entire system or a component of a system, may beembodied as an article of manufacture and maintained or provided as partof a computer-readable medium as defined previously. Another form of thesoftware may include signals that transmit program code of the softwareto a recipient over a network or other communication medium. Thus, inone example, a computer-readable medium has a form of signals thatrepresent the software/firmware as it is downloaded from a web server toa user. In another example, the computer-readable medium has a form ofthe software/firmware as it is maintained on the web server. Other formsmay also be used.

“User”, as used herein, includes but is not limited to one or morepersons, software, computers or other devices, or combinations of these.

Some portions of the detailed descriptions that follow are presented interms of algorithms and symbolic representations of operations on databits within a memory. These algorithmic descriptions and representationsare the means used by those skilled in the art to convey the substanceof their work to others. An algorithm is here, and generally, conceivedto be a sequence of operations that produce a result. The operations mayinclude physical manipulations of physical quantities. Usually, thoughnot necessarily, the physical quantities take the form of electrical ormagnetic signals capable of being stored, transferred, combined,compared, and otherwise manipulated in a logic and the like.

It has proven convenient at times, principally for reasons of commonusage, to refer to these signals as bits, values, elements, symbols,characters, terms, numbers, or the like. It should be borne in mind,however, that these and similar terms are to be associated with theappropriate physical quantities and are merely convenient labels appliedto these quantities. Unless specifically stated otherwise, it isappreciated that throughout the description, terms like processing,computing, calculating, determining, displaying, or the like, refer toactions and processes of a computer system, logic, processor, or similarelectronic device that manipulates and transforms data represented asphysical (electronic) quantities.

Example methods may be better appreciated with reference to flowdiagrams. While for purposes of simplicity of explanation, theillustrated methodologies are shown and described as a series of blocks,it is to be appreciated that the methodologies are not limited by theorder of the blocks, as some blocks can occur in different orders and/orconcurrently with other blocks from that shown and described. Moreover,less than all the illustrated blocks may be required to implement anexample methodology. Blocks may be combined or separated into multiplecomponents. Furthermore, additional and/or alternative methodologies canemploy additional, not illustrated blocks.

Elements illustrated in the flow diagrams denote “processing blocks”that may be implemented in logic. In one example, the processing blocksmay represent executable instructions that cause a computer, processor,and/or logic device to respond, to perform an action(s), to changestates, and/or to make decisions. Thus, the described methodologies canbe implemented as processor executable instructions and/or operationsprovided by a computer-readable medium. In another example, theprocessing blocks may represent functions and/or actions performed byfunctionally equivalent circuits such as an analog circuit, a digitalsignal processor circuit, an application specific integrated circuit(ASIC), or other logic device.

The flow diagrams of FIGS. 1 and 2, are not intended to limit theimplementation of the described examples. Rather, the diagramsillustrate functional information one skilled in the art could use todesign/fabricate circuits, generate software, or use a combination ofhardware and software to perform the illustrated processing. It will beappreciated that electronic and software applications may involvedynamic and flexible processes and thus blocks may be performedconcurrently, substantially in parallel, and/or at substantiallydifferent points in time.

FIG. 1 illustrates an example computer-implemented method 100 that isassociated with transportation planning in light of drop trailerarrangements. As used herein, transportation planning refers tocomputer-based determining of how and when to ship items using vehicleslike trucks that may have a leave-behind and/or pickup capability like adrop trailer arrangement available at a location. Method 100 mayinclude, at 110, receiving a set of orders. An order may describe, forexample, an item(s) that is to be delivered to a facility. How, when,how much to deliver, and so on may be described by order requirementsassociated with the order. Order requirements may include, for example,an earliest time at which the order may be picked up, a latest time atwhich the order may be picked up, the earliest time at which the ordercan be delivered, the latest time at which the order can be delivered, asource location for the order, and a destination for the order.

Method 100 may also include, at 120, accessing a transportation planningmodel. The transportation model may include, for example, informationconcerning modes by which an order may be shipped like a parcel mode, aless than truckload mode, a truckload mode, and so on. Thetransportation model may also include information concerning carriers bywhich an order can be delivered to a facility. The carriers may include,for example, parcel carriers, less than truckload carriers, truckloadcarriers, and so on. In some cases, a facility and a carrier may have adrop trailer arrangement whereby a trailer may be left at a facility.Thus, a driver may drop a first trailer at a facility and pick up asecond trailer at the facility without waiting around for the firsttrailer to be (un)loaded. Therefore, the transportation planning modelmay also include data concerning drop trailer arrangements betweenfacilities, carriers, and so on. The transportation planning model mayalso include, for example, rates charged by the carriers to carry anitem(s) according to the modes, facilities from which items are carried,facilities to which the items are carried, consolidation points throughwhich items pass, cross-docking locations across which items pass, atransportation network (e.g., roads) upon which the carriers travel, andso on.

Method 100 may also include, at 130, selectively consolidating ordersinto shipments. Whether orders are consolidated into shipments maydepend on factors like common origins, common destinations, requirementsthat sets of items remain together in transit, requirements that sets ofitems be delivered together, the existence of an under-utilized truckmoving along a path that satisfies the order, and so on. In method 100,the consolidation may also depend, at least in part, on the availabilityof a drop trailer arrangement as described in the transportationplanning model.

Method 100 may also include, at 140, selectively assigning a shipment(s)to a load. The load may be, for example, a multi-stop load. Whethershipments are assigned to loads may depend on factors like commonorigins, common destinations, common pickup windows, common deliverywindows, and so on. For multi-stop loads, whether shipments are assignedto loads may depend on factors like the proximity of origins, theproximity of destinations, compatibilities involving commodities,equipment, carriers, facilities, and so on. In method 100, theassignment may also depend, at least in part, on the availability of adrop trailer action as described in the transportation planning model.Thus in method 100, a load may include a drop trailer action. By way ofillustration, due to the allowed time windows for pickup and/ordelivery, the compatibility of different shipments for inclusion on thesame multi-stop load may depend on whether a drop trailer arrangementcan be utilized at the origin(s) and/or destination(s) of a shipment(s).

Method 100 may also include, at 150, providing an actionable plan ofloads for delivering shipments to facilities. The actionable plan may beprovided, for example, on a computer-readable medium like a disk, a CD,a DVD, and so on. In one example, the actionable plan and/or portionsthereof may be distributed to carriers by, for example, the Internet. Inthis case, the computer-readable medium may take the form of a carrierwave. The loads may be described by data including, for example, a starttime, a start location, a sequenced set of stops, a drop trailerinstruction, a pickup trailer instruction, and a set of shipmentsinvolved in the load. It is to be appreciated that in some examples aload may include multiple stops, that some items may be dropped off at astop and that other items may be picked up at a stop. Furthermore, it isto be appreciated that a load as provided by method 100 may include adrop trailer action whereby a trailer is either dropped off and/orpicked up at a stop. Most often a trailer will be picked up or droppedoff at the first or last stop.

In some examples, the actionable plan provided by method 100 improves onconventional actionable plans because it includes drop trailerarrangements and thus may include more efficient multi-stop loads thatmay not have appeared feasible or that may have appeared less desirableif not for considering drop trailer arrangements. Thus, in one example,the actionable plan may facilitate improving a utility measurementassociated with satisfying the set of orders as compared to anactionable plan that does not consider drop trailer actions. In anotherexample, the actionable plan may facilitate optimizing a utilitymeasurement associated with satisfying the set of orders. The utilitymeasurement may consider the relative and overall value of factors likereducing load cost, reducing order cost, improving order compliance withrules, laws, preferences (e.g., shipper preference, carrier preference,receiver preference, driver preference), improving truck utilizationpercentages, reducing spoilage, reducing breakage, improving on timedelivery, and so on. Reducing costs may include, for example, reducingthe total number of miles traveled, acquiring a lower unit cost for anorder, moving an order from a parcel mode to a truckload mode, moving anorder from a less than truckload mode to a truckload mode, and so on.

In one example, a decision concerning whether to consolidate an order(s)into a shipment(s) includes identifying consolidation opportunities. Indifferent examples, consolidation opportunities may include, forexample, a simple consolidation opportunity, a single tier poolingopportunity, a multi-tier pooling opportunity, a cross dockingopportunity, and a multi-stop load opportunity. Examples of theseconsolidation opportunities are described in association with FIGS. 8and 9.

As is known in the art, there are a variety of algorithms and processesby which items can be selected to be included or not included in a grouplike a consolidated order and/or multi-stop load. However, thesealgorithms conventionally may not have considered the possibility ofdrop trailer arrangements and their effect on the selection process. Thealgorithms may be implemented, for example, in processes including, butnot limited to, linear programming consolidation processes, simplexmethod consolidation processes, dynamic programming consolidationprocesses, greedy algorithm consolidation processes, look aheadconsolidation processes, divide and conquer consolidation processes,branch and bound processes, savings-based processes, heuristic-basedprocesses, and the like.

Dynamic programming is used to solve optimization problems that mayrequire testing many possible solutions. When presented with a set oforders, many possible solutions for consolidation, routing, loadassignment, and so on may be available. Conventionally, dynamicprogramming techniques may not have factored in the availability ofdrop-trailer arrangements when calculating acceptable and/or optimalsolutions in the transportation planning field. Thus, example systemsand methods described herein include in the solutions for transportationplanning problems the possibility that a drop trailer arrangement mayexist.

Dynamic programming involves breaking problems into dependentsub-problems, solving the sub-problems, and saving the solutions toreuse when applicable. Example systems and methods described herein mayinclude in the sub-problems considering the affect of a drop-trailerarrangement on a consolidation, routing, and/or assignment sub-problem.For example, one sub-problem may include identifying routes that includeexactly one drop-trailer arrangement while another sub-problem mayinvolve identifying all orders destined for a location that has a droptrailer arrangement. In dynamic programming, the single best solution isreferred to as the optimal solution. In some examples, neither the timenor the computing cycles may be available to compute an optimalsolution. In other examples, a sub-optimal solution may be acceptable,particularly if it can be computed within a desired time frame. Thus,example systems and methods described herein may employ dynamicprogramming solutions that are configured to produce a “good-enough”solution that may then be improved by considering available drop-trailerarrangements. While dynamic programming is described, it is to beappreciated that similar improvements may be made in other techniqueslike greedy algorithms, divide and conquer, and so on.

Greedy algorithms concern a general algorithm design paradigm that restson the consideration of configurations and objective functions. Aconfiguration describes different choices to make, different collectionsto assemble, different values to find, and so on. An objective functiondescribes a score that may be assigned to candidate configurations.Thus, transportation planning may employ greedy algorithms whoseobjective functions concern cost and/or utility and whose configurationsdescribe orders, consolidations, routes, assignments, and so on. Greedyalgorithms seek to maximize or minimize the objective function. A greedyalgorithm builds a solution by keeping the best result for a smallerproblem and adding that result to a current sub-solution. One examplesmaller problem may be identifying loads that violate an hours ofservice rule and another smaller problem may be identifying trucks thatare under-utilized. A greedy algorithm tends to make the best choice atthe moment in the hope that this will lead to an optimal and/oracceptable solution in the long run. Example greedy algorithms includeDijkstra's shortest path algorithm, Prim/Kruskal's MST algorithm, and soon. Greedy algorithms are typically employed to solve task schedulingand knapsack like problems. When considering drop-trailer arrangements,greedy algorithms may be adapted by reconfiguring the objective functionto reward drop trailer arrangements, to penalize missed drop-traileropportunities, by adding parameters to the configurations thatdiscourage certain immediate choices, and so on.

In one example, a greedy (or other) type of algorithm may be modified toeither narrow or widen the choices available at any point in the processto reflect the impact of drop trailer arrangements and to rewarddecisions that put a drop trailer opportunity into the proper position(e.g., first stop, last stop) within a load. Thus, by considering droptrailer arrangements, greedy and other algorithms may be able toidentify opportunities for loads that are superior (e.g., more costeffective, higher utility) than those possible in the absence of droptrailer arrangements.

A look ahead algorithm does not necessarily make the best choice at themoment, but rather makes “tentative” decisions and determines the bestresult based on subsequent decisions. Look ahead algorithms are familiarto those involved in chess programming. Divide and conquer programminginvolves breaking problems into independent sub-problems and solving thesub-problems. Linear programming is used to solve problems that involvelimited resources, an overall objective, and a choice of actions to betaken. The simplex method is a pre-eminent tool in linear programming.

To accommodate drop-trailer actions, these and other conventionaltechniques may be updated to make selections based, for example, on thedesirability of including only one location with a drop trailerarrangement per set of shipments to facilitate leaving other droptrailer arrangements for subsequent consolidations, the desirability ofincluding at least one location with a drop trailer arrangement in a setof shipments, and so on. Additionally, and/or alternatively, decisionsmay not be made solely on the desirability of including drop trailerarrangements in a plan but also, for example, on the desirability ofplan decisions that become feasible in the presence of drop trailerarrangements. Similarly, these techniques may be updated to makeselections where at least one selection is “pre-selected” as a “last on”selection based on the availability of a drop-trailer arrangement atthat pre-selected location. While pre-selecting and so on, it is to beappreciated that these techniques may be altered in other manners toconsider drop-trailer arrangements. In one example, the availability ofdrop-trailer arrangements may be considered while initial consolidationsare being made. In another example, the availability of drop-trailerarrangements may be considered after initial consolidations have beenmade.

In one example, selectively assigning shipments to loads includesidentifying a routing opportunity for a shipment(s). A routingopportunity may include, for example, a single stop routing opportunity,a multi-stop routing opportunity, a continuous move opportunity, and soon. In method 100, a routing opportunity may include a drop-traileraction. A continuous move is a sequence of loads that a single vehiclecan serve as one mission. A continuous move may have empty movementsbetween loaded legs.

Once again, routing algorithms known in the art may include, but are notlimited to, linear programming routing processes, simplex method routingprocesses, dynamic programming routing processes, greedy algorithmrouting processes, look ahead routing processes, divide and conquerrouting processes, branch and bound processes, savings-based processes,heuristic-based processes, and so on. These algorithms may be updated toconsider drop trailer arrangements in routing like they were updated toconsider drop trailer arrangements in consolidation. For example, from aset of destinations a subset of destinations may be reserved as “finaldestinations” based on having drop trailer arrangements available.Similarly, from a set of sources, a subset of sources may be reserved as“initial sources” based on having drop trailer arrangements available.By way of illustration, in a divide and conquer approach, divisions maybe made in a manner that facilitates partitioning the “finaldestinations” with drop trailer arrangements so that a maximum number ofdivisions remain drop trailer capable. By way of further illustration,in a greedy algorithm approach, an immediate decision value may bemanipulated to receive a higher score if the immediate decision willcomplete a load and the immediate decision will add a drop trailerfacility to the end of the load while an immediate decision value may bemanipulated to receive a lower score if the immediate decision will notcomplete a load and the immediate decision will add a second droptrailer facility to a load that already includes a drop trailerfacility. It is to be appreciated that the updates to the divide andconquer algorithms and the greedy algorithms are merely examples andthat other updates may be employed.

Considering drop trailer arrangements in method 100 facilitates takingactions that are not conventionally possible. For example, method 100facilitates relaxing a constraint associated with facility operationtime. By way of illustration, conventionally a transportation planningmethod may include as a hard constraint the times at which a deliverymay be made at a facility or the times at which an order may be pickedup from a facility. If a drop trailer arrangement exists for thefacility and a carrier, these time constraints may in some cases beignored. These constraints may only need to be applied to live(un)loading since it may only occur during hours when a facility isstaffed, open for operations, and has available dock and workercapacity. Conversely, with appropriate drop trailer arrangements, atrailer may be dropped at other times for later (un)loading. Thisfacilitates eliminating a constraint from the consolidation and/orrouting algorithms and thus facilitates reducing the overall complexityof such algorithms. Furthermore, this facilitates making certaindecisions feasible that otherwise would not be, thus allowing a broaderset of solutions and potentially allowing the chosen solution to achievehigher values for relevant utility functions. Additionally, thisfacilitates making available at a lower cost and/or higher utility othersolutions that were feasible at a higher cost due, for example, tocharges related to delaying a truck and driver until a facility is open,staffed, and has capacity if the charges may be avoided if the truck anddriver do not have to wait.

While FIG. 1 illustrates various actions occurring in serial, it is tobe appreciated that various actions illustrated in FIG. 1 could occursubstantially in parallel. By way of illustration, a first process couldreceive orders, a second process could access a transportation planningmodel, a third process could consolidate orders to shipments, a fourthprocess could assign shipments to loads, and a fifth process couldprovide actionable load data. While five processes are described, it isto be appreciated that a greater and/or lesser number of processes couldbe employed and that lightweight processes, regular processes, threads,and other approaches could be employed.

In one example, methodologies are implemented as processor executableinstructions and/or operations stored on a computer-readable medium.Thus, in one example, a computer-readable medium may store processorexecutable instructions operable to perform a method that includesreceiving a set of orders that describe items to be delivered tofacilities as controlled, at least in part, by order requirements. Themethod may also include accessing a transportation planning model thatincludes information concerning modes and carriers by which an order canbe delivered to a facility. The transportation planning model may alsoinclude drop trailer arrangement data concerning the facilities and thecarriers. The method may also include selectively consolidating ordersinto shipments based, at least in part, on the transportation planningmodel and the availability of a drop trailer arrangement. The method mayalso include selectively assigning shipments to loads based, at least inpart, on the transportation planning model and the availability of adrop trailer action. Finally, the method may include providing anactionable plan of loads for delivering the shipments to the facilities.While the above method is described being stored on a computer-readablemedium, it is to be appreciated that other example methods describedherein can also be stored on a computer-readable medium.

FIG. 2 illustrates an example method 200 associated with transportationplanning in light of drop trailer arrangements. Method 200 includesactions 210 through 250 similar to actions 110 through 150 in method100. In method 200, consolidations may initially be made at 230 withoutconsidering drop trailer arrangements or, at 230, algorithms may bereconfigured to partially consider drop trailer arrangements. Thusmethod 200 may also include, at 260, re-examining consolidations toconsider drop-trailer arrangements. Similarly, at 240, assignments mayinitially be made without considering drop trailer arrangements. Thus,method 200 may also include, at 270, re-examining assignments toconsider drop-trailer arrangements. Thus, method 200 may be implementedto reconfigure an existing method or to re-optimize a plan based onadditional drop-trailer considerations. This may facilitate, forexample, determining an initial plan, communicating that plan tocarriers, and then responding to carrier information concerningdrop-trailer possibilities and re-optimizing the plan based on this“just in time” information.

FIG. 3 illustrates an example system 300 associated with transportationplanning in light of drop trailer arrangements. System 300 includes datastore 310 that is configured to store orders. An order describes anitem(s) to be delivered to a facility in accordance with an orderrequirement.

System 300 also includes a model logic 320 that is configured to accessa shipping model. The shipping model may describe, for example, shippingmodes, carriers, facilities, a transportation network, and drop trailerarrangements between the facilities and the carriers. Additionally, theshipping model may include data concerning factors relevant to shippingan item from a source to a destination like a transportation networkconfiguration, the capacity of various types of equipment, transit timesacross portions of the transportation network, commodity to commoditycompatibilities, commodity to equipment compatibilities, commodity tofacility compatibilities, commodity to carrier compatibilities, facilityto equipment compatibilities, rules for carriers, carrier limits, lawsconcerning hours of service for drivers and/or equipment, days on whicha facility may be open, hours during which a facility may operate, theavailability of equipment (e.g., tractors, trailers), the availabilityof drivers, the capacity of a facility, carrier pickup lead times, shipsets (e.g., groups of items that need to be shipped together), and soon.

System 300 may also include a consolidation logic 330 that is configuredto consolidate orders into shipments. The consolidation logic 330 may beoperably connected to data store 310 and model logic 320. Whether and/orhow orders are consolidated into shipments may depend, for example, onthe shipping model and the availability of drop trailer possibilities.In one example, consolidation logic 330 may be configured to identify aconsolidation opportunity and then to make consolidations based on theidentified opportunities. Opportunities may be identified using, forexample, a linear programming selection process, a simplex methodselection process, a dynamic programming selection process, a greedyselection process, a look ahead selection process, a divide and conquerselection process, a branch and bound process, a savings-based process,a heuristic-based process, and so on. In one example, consolidationlogic 330 may be configured to perform these processes in a manner thatconsiders the availability and/or affect of a drop-trailer arrangement.Opportunities may include, for example, simple consolidationopportunities, single tier pooling opportunities, multi-tier poolingopportunities, cross docking opportunities, multi-stop poolingopportunities, and so on.

System 300 may also include a load logic 340 that is configured toassign shipments to loads. Once again, whether and/or how shipments areassigned to loads may depend, at least in part, on the shipping modeland the availability of drop trailer possibilities. System 300facilitates determining loads that may include a drop trailer action. Inone example, including a drop trailer arrangement in a load mayfacilitate violating a facility operation time constraint described inthe shipping model.

In one example, load logic 340 may be configured to identify a routingopportunity using techniques like those described above (e.g., linearprogramming, simplex method, dynamic programming, greedy algorithms,divide and conquer). The routing opportunities identified by the loadlogic 340 may include, for example, single stop routes, multi-stoproutes, continuous moves, and so on. Load logic 340 may be configured toconsider drop-trailer arrangements as part of routing opportunities.Thus, load logic 340 may be configured to assign shipments to loadsbased, at least in part, on the routing opportunity and the availabilityof a drop trailer arrangement.

The following examples illustrate different results that may be achievedusing example systems and methods described herein when compared toconventional systems. Consider the following two orders. A first orderOD1 may concern an item available at facility 0 that is to be deliveredto facility D1. OD1 may have a pickup window on Monday from 9 am to 11am, and a flexible delivery window. A second order OD2 may concern anitem available at facility 0 that is to be delivered to facility D2. OD2may have a pickup window on Monday from 9 am to 11 am (the same as OD1)and a delivery time window of Tuesday from 8 am to 12 pm. Each order maytake one hour to load and each order may take one hour to unload. Allthree of the facilities, O, D1, and D2 are open twenty four hours fromMonday through Friday.

Now assume that a first carrier C1 provides a truckload (TL) servicefrom O to D1/D2 with the loaded-distance charge of $1/mile, and has alayover setting for maximum on duty time in any twenty four hour periodof fourteen hours with a weekday layover charge of $100. Also assumethat carrier C1 has a drop trailer arrangement with facility D2.

Assume that D1 is 200 miles from O and it takes 3 hours to drive from Oto D1. Assume that D2 is 170 miles from O and that it also takes 3 hoursto drive from 0 to D2. Further assume that D1 is 60 miles from D2 andthat it takes 1 hour to drive from D1 to D2 and from D2 to D1.Conventional systems that do not consider the drop trailer arrangementbetween carrier C1 and facility D2 would produce two sub-optimalsolutions. The first sub-optimal solution is a load from O to D1 to D2.The scheduling of this truckload is as follows (unit=hour):

The second sub-optimal solution is a load from O to D2 to D1. Thescheduling of this truckload is as follows (unit=hour):

A layover charge may be assessed if the truck physically arrives at D2with enough time to finish unloading during typically accepted “regularbusiness hours” (e.g., at 4 p.m. if regular hours last until 5 p.m.) butis not actually unloaded until the next day. A weekday layover charge istypically incurred when a truck arrives with enough time to finish(un)loading within defined regular business hours but is delayed untilthe next business day due to other factors like, in this case, theallowed delivery window for the order.

A conventional system that does not consider the drop-trailerarrangement will select the second load as the best choice, even thoughit is sub-optimal. Example systems and methods described herein,however, will consider the drop trailer arrangement between carrier C1and facility D2. When considering the drop trailer arrangement, twoloads may be examined. A first load starts at O and proceeds in order toD1 and D2. Since carrier C1 has a drop trailer arrangement with facilityD2, and D2 is the last stop in this load, when the driver reaches D2,the driver can immediately drop the trailer and ignore the earlydelivery time associated with order OD2. Thus, the layover charge atfacility D2 is avoided.

The scheduling of this truckload will now be as follows:

A second load that will be considered starts at O and proceeds in orderfrom D2 to D1. Since D2 is not the last stop, the drop trailerarrangement between C1 and D2 can not be used and thus the schedulingand the total cost of this truckload will be the same as that in aconventional system where Total cost=distance charge+layovercost=$1*(170+60)+$100=$330. Thus, by considering the drop-trailerarrangement, a lower cost of $260 is found and a drop-trailerarrangement will be used. In this example, the consolidation, routing,and/or assignment algorithms may have operated in a typical manner.However by simply adding the consideration of drop-trailer arrangements,a lower cost was found. In other examples, the algorithms may have beenreconfigured to operate differently. For example, the algorithms mayhave reserved certain destinations as “final destinations”, or may haveidentified certain destinations as “preferred destinations” based on theavailability of a drop trailer arrangement.

A second example illustrates another way in which example systems andmethods may provide improvements over conventional systems that do notconsider drop trailer arrangements. Consider two orders, both of whichwill take one hour to load, five hours to drive, and two hours to unloadand each of which may utilize forty five percent of a truck's capacity.The first order originates at O and goes to destination D1. The secondorder originates at O and goes to destination D2. Each of these loadswould take eight hours to complete in isolation. Now consider that itmay take one hour to drive from D1 to D2 or from D2 to D1. Also considerthat a drop trailer arrangement may exist at D2, that a driver may berestricted to 10.5 hours on duty (e.g., driving, (un)loading, waiting)in a day and that both the first order and the second order must bedelivered on the same day that they are picked up.

A conventional system would likely schedule two trucks, each of whichwould have forty five percent space utilization and each of which woulduse eight hours of the 10.5 available on-duty hours. If the drop trailerarrangement is not considered, two trucks would be required because asingle driver could not complete both orders on the same day whilestaying at or below 10.5 hours of service. But example systems andmethods would likely schedule a single truck that first goes to D1 andthen to D2 and simply drops the trailer at D2. The single truck wouldhave ninety percent utilization, would use ten of the 10.5 availableon-duty hours and would likely have an overall lower cost whileimproving utility.

FIG. 4 illustrates an example system 400 associated with transportationplanning in light of drop trailer arrangements. System 400 includescomponents 410 through 440 similar to components 310 through 340.Additionally, system 400 may include a re-evaluation logic 450 that isconfigured to reconfigure a load based on the availability of a droptrailer arrangement. For example, a conventional system may produce anactionable plan of loads. It may be unwieldy and/or impossible toreconfigure the algorithms used by the conventional system forconsolidation, routing, and/or assignment. Thus, re-evaluation logic 450may be provided to facilitate examining the actionable plan provided bythe conventional system to identify any optimizing possibilitiesassociated with drop trailer arrangements.

FIG. 5 illustrates an example computing device in which example systemsand methods described herein, and equivalents, can operate. The examplecomputing device may be a computer 500 that includes a processor 502, amemory 504, and input/output ports 510 operably connected by a bus 508.In one example, the computer 500 may include a planning logic 530 thatis configured to facilitate transportation planning in light of droptrailer arrangements. Planning logic 530 may implement portions ofexample systems described herein and may execute portions of examplemethods described herein. Thus, whether implemented in hardware,software, firmware, and/or combinations thereof, planning logic 530 andcomputer 500 may provide means for analyzing a transportation model thatincludes drop trailer arrangement data, means for determining how ordersmay be grouped together into shipments based, at least in part, on thetransportation model and possible drop trailer arrangements, means fordetermining how shipments may be routed together into loads based, atleast in part, on the transportation model and possible drop traileractions, and means for providing a set of instructions concerning theloads.

Generally describing an example configuration of computer 500, processor502 can be a variety of various processors including dual microprocessorand other multi-processor architectures. Memory 504 can include volatilememory and/or non-volatile memory. Disk 506 may be operably connected tocomputer 500 via, for example, an input/output interface (e.g., card,device) 518 and an input/output port 510. Disk 506 can include, but isnot limited to, devices like a magnetic disk drive, a solid state diskdrive, a floppy disk drive, a tape drive, a Zip drive, a flash memorycard, and/or a memory stick. Furthermore, disk 506 can include opticaldrives like a CD-ROM, a CD recordable drive (CD-R drive), a CDrewriteable drive (CD-RW drive), and/or a digital video ROM drive (DVDROM). The memory 504 can store processes 514 and/or data 516, forexample. Disk 506 and/or memory 504 can store an operating system thatcontrols and allocates resources of computer 500.

Bus 508 can be a single internal bus interconnect architecture and/orother bus or mesh architectures. While a single bus is illustrated, itis to be appreciated that computer 500 may communicate with variousdevices, logics, and peripherals using other busses that are notillustrated (e.g., PCIE, SATA, Infiniband, 1394, USB, Ethernet).

Computer 500 may interact with input/output devices via i/o interfaces518 and input/output ports 510. Input/output devices can include, butare not limited to, a keyboard, a microphone, a pointing and selectiondevice, cameras, video cards, displays, disk 506, network devices 520,and the like. Input/output ports 510 can include but are not limited to,serial ports, parallel ports, and USB ports.

Computer 500 can operate in a network environment and thus may beconnected to network devices 520 via i/o devices 518, and/or i/o ports510. Through network devices 520, computer 500 may interact with anetwork. Through the network, computer 500 may be logically connected toremote computers. The networks with which computer 500 may interactinclude, but are not limited to, a local area network (LAN), a wide areanetwork (WAN), and other networks. Network devices 520 can connect toLAN technologies including, but not limited to, fiber distributed datainterface (FDDI), copper distributed data interface (CDDI), Ethernet(IEEE 802.3), token ring (IEEE 802.5), wireless computer communication(IEEE 802.11), Bluetooth (IEEE 802.15.1), and the like. Similarly,network devices 520 can connect to WAN technologies including, but notlimited to, point to point links, circuit switching networks likeintegrated services digital networks (ISDN), packet switching networks,and digital subscriber lines (DSL).

Referring now to FIG. 6, information can be transmitted between variouscomputer components and/or logics associated with transportationplanning in light of drop trailer arrangements as described herein via adata packet 600. Data packet 600 may be employed, for example, tocommunicate data associated with a load. The data packet 600 includes aheader field 610 that includes information like the length and type ofpacket. A source identifier 620 follows the header field 610 andincludes, for example, an address of the computer component and/or logicfrom which the packet 600 originated. Following the source identifier620, the packet 600 includes a destination identifier 630 that holds,for example, an address of the computer component and/or logic to whichthe packet 600 is ultimately destined. Source and destinationidentifiers can be, for example, a globally unique identifier (GUID), auniform resource locator (URLs), a path name, and the like. The datafield 640 in the packet 600 includes various information intended forthe receiving computer component and/or logic. The data packet 600 endswith an error detecting and/or correcting field 650 whereby a computercomponent and/or logic can determine if it has property received thepacket 600. While five fields are illustrated in a certain order, it isto be appreciated that a greater and/or lesser number of fields arrangedin different orders can be present in example data packets.

FIG. 6 also illustrates sub-fields 660 within the data field 640. Thesubfields 660 discussed are merely exemplary and it is to be appreciatedthat a greater and/or lesser number of sub-fields could be employed withvarious types of data germane to transportation planning in light ofdrop trailer arrangements. In one example, data packet 600 may beemployed to transmit load data to, for example, a carrier. Thus, thesub-fields 660 include a first field 662 that holds, for example, asource data like an origination point, a pickup window, and so on.Sub-fields 660 may also include a second field 664 that holds, forexample, a sequence of stops data including, for example, delivery timewindows, shipment(s) to be delivered at the stop, and so on. Sub-fields660 may also include a third field 666 that holds, for example, a droptrailer arrangement data. For example, the drop trailer arrangement datamay include directions concerning “open hours” arrivals, “closed hour”arrivals, a trailer to drop, a trailer to pick up, and so on.

Referring now to FIG. 7, an application programming interface (API) 700is illustrated providing access to a system 710 for transportationplanning in light of drop trailer arrangements. API 700 can be employed,for example, by a programmer 720 and/or a process 730 to gain access toprocessing performed by system 710. For example, a programmer 720 canwrite a program to access system 710 (e.g., invoke its operation,monitor its operation, control its operation) where writing the programis facilitated by the presence of API 700. Rather than programmer 720having to understand the internals of system 710, programmer 720 merelyhas to learn the interface to system 710. This facilitates encapsulatingthe functionality of system 710 while exposing that functionality.

API 700 can be employed to provide data values to system 710 and/orretrieve data values from system 710. For example, a process 730 thatidentifies consolidation opportunities can provide consolidation data tosystem 710 via API 700 by, for example, using a call provided in API700. Thus, in one example of API 700, a set of application programminginterfaces can be stored on a computer-readable medium. The interfacescan include, but are not limited to, a first interface 740 thatcommunicates an order data including, for example, commodity data, apickup window, a delivery window, an origin, a destination, and so on.The interfaces may also include a second interface 750 that communicatesa shipment data including, for example, a set of orders, a pickupwindow, a delivery window, an origin, a destination, and so on. Theinterfaces may also include a third interface 760 that communicates aload data including, for example, a start time, a sequence of stops, andso on. The interfaces may also include a fourth interface 770 forcommunicating a drop trailer arrangement data including, for example,“while open” instructions, “while closed” instructions, a drop offtrailer identifier, a pick up trailer identifier, and so on.

FIG. 8 illustrates example pooling possibilities. Pooling possibilitiesmay include, for example, simple consolidation 810 where orders with acommon source and destination are placed on the same truck. Poolingpossibilities may also include single tier pooling like inbound pooling820 where orders for a common destination are brought to a consolidationpoint, consolidated, and sent to the common destination. Poolingpossibilities may also include outbound pooling 830 where orders havinga common source but different destinations are sent to a deconsolidationpoint and then broken down into smaller shipments. Pooling may alsoinclude multi-tier pooling 840 and cross-docking 850. While conventionalsystems and methods may investigate pooling possibilities whenperforming transportation planning, their investigations may neglectdrop-trailer arrangements.

FIG. 9 illustrates other load scenarios. These possibilities include,for example, multi-stop load 910 and compound pooling, multi-stop load920. In 910, a truck may make four stops including a pickup at A, anddeliveries at B, C, and D. Additionally, at D, rather than live(un)loading, the trailer may be dropped off and another trailer may bepicked up. In 920, a truck may make a pickup at Q, a delivery of asingle shipment at R, a delivery of several shipments for severaldifferent destinations at deconsolidation point S, and then drop thetrailer at T.

While example systems, methods, and so on have been illustrated bydescribing examples, and while the examples have been described inconsiderable detail, it is not the intention of the applicants torestrict or in any way limit the scope of the appended claims to suchdetail. It is, of course, not possible to describe every conceivablecombination of components or methodologies for purposes of describingthe systems, methods, and so on described herein. Additional advantagesand modifications will readily appear to those skilled in the art.Therefore, the invention is not limited to the specific details, therepresentative apparatus, and illustrative examples shown and described.Thus, this application is intended to embrace alterations,modifications, and variations that fall within the scope of the appendedclaims. Furthermore, the preceding description is not meant to limit thescope of the invention. Rather, the scope of the invention is to bedetermined by the appended claims and their equivalents.

To the extent that the term “includes” or “including” is employed in thedetailed description or the claims, it is intended to be inclusive in amanner similar to the term “comprising” as that term is interpreted whenemployed as a transitional word in a claim. Furthermore, to the extentthat the term “or” is employed in the detailed description or claims(e.g., A or B) it is intended to mean “A or B or both”. When theapplicants intend to indicate “only A or B but not both” then the term“only A or B but not both” will be employed. Thus, use of the term “or”herein is the inclusive, and not the exclusive use. See, Bryan A.Garner, A Dictionary of Modern Legal Usage 624 (2d. Ed. 1995).

1. A computer-implemented method, comprising: receiving a set of ordersthat describe one or more items to be delivered to one or morefacilities as controlled, at least in part, by one or more orderrequirements; accessing a transportation planning model that includesinformation concerning one or more modes and one or more carriers bywhich an order can be delivered to a facility, the transportationplanning model also including drop trailer arrangement data concerningthe facilities and the carriers; selectively consolidating one or moreorders into one or more shipments based, at least in part, on thetransportation planning model and the availability of a drop trailerarrangement; selectively assigning one or more shipments to one or moreloads based, at least in part, on the transportation planning model andthe availability of a drop trailer action, where a load may include adrop trailer action; and providing an actionable plan of loads fordelivering the one or more shipments to the one or more facilities. 2.The method of claim 1, where the actionable plan facilitates improving autility measurement associated with satisfying the set of orders ascompared to an actionable plan that does not consider drop traileractions.
 3. The method of claim 1, where the actionable plan facilitatesoptimizing a utility measurement associated with satisfying the set oforders.
 4. The method of claim 1, where the order requirements includeone or more of, an earliest pickup time, an earliest delivery time, alatest pickup time, a latest delivery time, a source, and a destination.5. The method of claim 1, where the transportation planning modelincludes data concerning one or more of, the modes, the carriers, rates,the facilities, and a transportation network.
 6. The method of claim 1,where selectively consolidating one or more orders into one or moreshipments includes identifying a consolidation opportunity using one ormore of, a linear programming consolidation process, a simplex methodconsolidation process, a dynamic programming consolidation process, agreedy consolidation process, a look ahead consolidation process, adivide and conquer consolidation process, a branch and bound process, asavings-based process, and a heuristic-based process.
 7. The method ofclaim 6, where a consolidation opportunity includes one or more of, asimple consolidation opportunity, a single tier pooling opportunity, amulti-tier pooling opportunity, a cross docking opportunity, amulti-stop load opportunity, a continuous move opportunity, and acompound multi-stop load opportunity.
 8. The method of claim 1, whereselectively assigning one or more shipments to one or more loadsincludes identifying a routing opportunity using one or more of, alinear programming routing process, a simplex method routing process, adynamic programming routing process, a greedy routing process, a lookahead routing process, a divide and conquer routing process, a branchand bound process, a savings-based process, and a heuristic-basedprocess.
 9. The method of claim 8, where a routing opportunity includesone or more of, a single stop route opportunity, a multi-stop routeopportunity, and a continuous move opportunity, where a routingopportunity may include a drop-trailer action.
 10. The method of claim1, where a load is described by a load data that includes one or moreof, a start time, a start location, a sequenced set of stops, a droptrailer instruction, a pickup trailer instruction, and a set ofshipments.
 11. The method of claim 2, where improving the utilitymeasurement includes one or more of, reducing a load cost, reducing anorder cost, improving order compliance with one or more of, a rule, alaw, and a preference, improving truck percentage utilization, reducinga spoilage amount, reducing a breakage amount, and improving on timedelivery.
 12. The method of claim 11, where reducing an order costincludes one or more of, acquiring a lower unit cost for an order,moving an order from a parcel mode to a truckload mode, and moving anorder from a less than truckload mode to a truckload mode.
 13. Themethod of claim 3, where optimizing the utility measurement includes oneor more of, reducing a load cost, reducing an order cost, improvingorder compliance with one or more of, a rule, a law, and a preference,improving truck percentage utilization, reducing a spoilage amount,reducing a breakage amount, and improving on time delivery.
 14. Themethod of claim 13, where reducing an order cost includes one or moreof, acquiring a lower unit cost for an order, moving an order from aparcel mode to a truckload mode, and moving an order from a less thantruckload mode to a truckload mode.
 15. The method of claim 1, includingrelaxing a constraint associated with facility operation times based, atleast in part, on considering a drop trailer action.
 16. The method ofclaim 1, the actionable plan being stored on a computer-readable medium.17. The method of claim 1, where a load may be reconfigured after it isestablished based on analyzing a drop trailer arrangement dataconcerning the facility and the carrier associated with the load. 18.The method of claim 1, where a load may initially be configured based,at least in part, on analyzing drop trailer arrangement data concerningthe facilities and the carriers available for the load.
 19. The methodof claim 1 being stored as computer executable instructions on acomputer-readable medium.
 20. A computer-implemented method, comprising:receiving a set of orders that describe one or more items to bedelivered to one or more facilities as controlled, at least in part, byone or more order requirements, where the order requirements include oneor more of, an earliest pickup time, an earliest delivery time, a latestpickup time, a latest delivery time, a pickup source, and a deliverydestination; accessing a transportation planning model that includesinformation concerning one or more modes and one or more carriers bywhich an order can be delivered to a facility, the transportation modelalso including drop trailer arrangement data concerning the facilitiesand the carriers, where the transportation planning model includes dataconcerning one or more of, the modes, the carriers, rates, thefacilities, and a transportation network; selectively consolidating oneor more orders into one or more shipments based, at least in part, onthe transportation model and the availability of a drop trailerarrangement, where selectively consolidating one or more orders into oneor more shipments includes identifying a consolidation opportunity usingone or more of, a linear programming consolidation process, a simplexmethod consolidation process, a dynamic programming consolidationprocess, a greedy consolidation process, a look ahead consolidationprocess, a divide and conquer consolidation process, a branch and boundprocess, a savings-based process, and a heuristic-based process, where aconsolidation opportunity includes one or more of, a simpleconsolidation opportunity, a single tier pooling opportunity, amulti-tier pooling opportunity, a cross docking opportunity, acontinuous move opportunity, a multi-stop load opportunity, and acompound multi-stop load opportunity; selectively assigning one or moreshipments to one or more loads based, at least in part, on thetransportation model and the availability of a drop trailer arrangement,where a load may include a drop trailer action, where selectivelyassigning one or more shipments to one or more loads includesidentifying a routing opportunity using one or more of, a linearprogramming routing process, a simplex method routing process, a dynamicprogramming routing process, a greedy routing process, a look aheadrouting process, a divide and conquer routing process, a branch andbound process, a savings-based process, and a heuristic-based process,where a routing opportunity includes one or more of, a single stop routeopportunity, a multi-stop route opportunity, and a continuous moveopportunity, and where a routing opportunity may include a drop-trailerarrangement; and providing an actionable plan of loads for deliveringthe one or more shipments to the one or more facilities, where theactionable plan facilitates one or more of, improving a utilitymeasurement associated with satisfying the set of orders as compared toan actionable plan that does not consider drop trailer actions, andoptimizing a utility measurement associated with satisfying the set oforders, where improving the utility measurement includes one or more of,reducing a load cost, reducing an order cost, improving order compliancewith one or more of a rule, a law, and a preference, improving truckpercentage utilization, reducing a spoilage amount, reducing a breakageamount, and improving on time delivery, where reducing an order costincludes one or more of, acquiring a lower unit cost for an order,moving an order from a parcel mode to a truckload mode, and moving anorder from a less than truckload mode to a truckload mode, where a loadmay initially be configured based, at least in part, on analyzing droptrailer arrangement data concerning the facilities and the carriers andwhere a load may be reconfigured after it is established based onanalyzing drop trailer arrangement data concerning the facilities andthe carriers.
 21. A system, comprising: a data store configured to storean order that describes an item to be delivered to a facility inaccordance with an order requirement; a model logic configured to accessa shipping model, where the shipping model describes shipping modes,carriers, facilities, a transportation network, and drop trailerarrangements between the facilities and the carriers; a consolidationlogic operably connected to the data store and the model logic, theconsolidation logic being configured to consolidate orders intoshipments based, at least in part, on the shipping model and theavailability of drop trailer possibilities; and a load logic operablyconnected to the consolidation logic and the model logic, the load logicbeing configured to assign shipments to loads based, at least in part,on the shipping model and the availability of drop trailerpossibilities, where a load may include a drop trailer action thatfacilitates violating a facility operation time constraint described inthe shipping model.
 22. The system of claim 21, where the shipping modelincludes data concerning one or more of, drop trailer arrangements,transportation network configuration, equipment capacity, transit times,commodity-commodity compatibility, commodity-equipment compatibility,commodity-facility compatibility, commodity-carrier compatibility,facility-equipment compatibility, carrier rules, carrier limits, hoursof service laws, facility operation days, facility operation hours,equipment availability, driver availability, facility capacity, carrierpickup lead times, and elements of an order that are supposed to remaintogether throughout the time and geographical extent that the elementsare in transit.
 23. The system of claim 22, where the consolidationlogic is configured to identify a consolidation opportunity using one ormore of, a linear programming selection process, a simplex methodselection process, a dynamic programming selection process, a greedyselection process, a look ahead selection process, a divide and conquerselection process, a branch and bound process, a savings-based process,and a heuristic-based process, where a consolidation opportunityincludes one or more of, a simple consolidation opportunity, a singletier pooling opportunity, a multi-tier pooling opportunity, a crossdocking opportunity, a multi-stop load opportunity, a continuous moveopportunity, and a compound multi-stop load opportunity; and where theconsolidation logic consolidates orders based, at least in part, on theconsolidation opportunities.
 24. The system of claim 23, where the loadlogic is configured to identify a routing opportunity using one or moreof, a linear programming process routing, a simplex method routingprocess, a dynamic programming routing process, a greedy routingprocess, a look ahead routing process, a divide and conquer routingprocess, a branch and bound process, a savings-based process, and aheuristic-based processes, where a routing opportunity includes one ormore of, a single stop route opportunity, a multi-stop routeopportunity, and a continuous move opportunity, and where a routingopportunity may include a drop-trailer arrangement, and where the loadlogic assigns shipments to loads based, at least in part, on the routingopportunity.
 25. The system of claim 24, including a re-evaluation logicconfigured to reconfigure a load based on the availability of a droptrailer arrangement.
 26. A system, comprising: means for analyzing atransportation model that includes drop trailer arrangement data; meansfor determining how orders may be grouped together into shipments based,at least in part, on the transportation model and possible drop trailerarrangements; means for determining how shipments may be groupedtogether into loads based, at least in part, on the transportation modeland possible drop trailer actions; and means for providing a set ofinstructions concerning the loads.
 27. A data packet for transmitting aload data, comprising: a first field that stores a source data; a secondfield that stores a sequence of stops data; and a third field thatstores a drop trailer arrangement data.
 28. A set of applicationprogramming interfaces embodied on a computer-readable medium forexecution by a computer component in conjunction with optimizingtransportation planning based, at least in part, on drop trailerarrangements, comprising: a first interface for communicating an orderdata; a second interface for communicating a shipment data; a thirdinterface for communicating a load data; and a fourth interface forcommunicating a drop trailer arrangement data.